datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Medical-Reasoning-SFT-GPT-OSS-120B-V2
Medical-Reasoning-SFT-GPT-OSS-120B-V2
A large-scale medical reasoning dataset generated using openai/gpt-oss-120b, containing over 506,000 samples with detailed chain-of-thought reasoning for medical and healthcare questions.
GPT-OSS-120B is OpenAI's state-of-the-art open-weight model, achieving near-parity with closed models on reasoning benchmarks while being Apache 2.0 licensed.
Dataset Overview
Metric
Value
Model
openai/gpt-oss-120b
Total Samples
506… See the full description on the dataset page: https://huggingface.co/datasets/OpenMed/Medical-Reasoning-SFT-GPT-OSS-120B-V2.gpt-oss-120b-reasoning-STEM-5K
GPT-OSS-120B-Distilled-Reasoning-STEM Dataset
1) Dataset Overview
Data Source Model: gpt-oss-120b-high
Task Type: STEM Reasoning and Problem Solving (Science, Technology, Engineering & Mathematics)
Data Format: `JSON Lines
Fields: generator, category, input, CoT_Native——reasoning, answer
(Consistent with the math dataset, splitting the original 'output' into 'reasoning' and 'answer' for COT/SFT scenarios.)
2) Design Goals (Motivation)
This dataset targets… See the full description on the dataset page: https://huggingface.co/datasets/Jackrong/gpt-oss-120b-reasoning-STEM-5K.Superior-Reasoning-SFT-gpt-oss-120b-split-en
Superior-Reasoning SFT (stage1 + stage2) with <think> split and English filtering
Summary
This dataset is a processed derivative of Alibaba-Apsara/Superior-Reasoning-SFT-gpt-oss-120b (subsets stage1 and stage2, train split). It restructures each example into three fields:
input: the original input
reasoning: the content extracted from <think> ... </think> within the original output (inner text only)
output: the remainder of the original output after removing all <think>… See the full description on the dataset page: https://huggingface.co/datasets/Hugodonotexit/Superior-Reasoning-SFT-gpt-oss-120b-split-en.nemotron-nano2-safety-distill-gptoss
Nemotron Nano 2 Safety Distill — GPT-OSS
A distilled safety dataset produced using the Nemotron Nano 2 recipe with GPT-OSS-20B and GPT-OSS-120B as teacher models.
⚠️ Content Warning: This dataset includes potentially harmful prompts. Use responsibly for research purposes only.
Overview
This safety-focused distilled dataset was created by following the Nemotron Nano 2 safety recipe, adapted to use GPT-OSS-20B and GPT-OSS-120B as teacher models. Due to resource limitations… See the full description on the dataset page: https://huggingface.co/datasets/Ericwang/nemotron-nano2-safety-distill-gptoss.GPT-OSS-120B-Distilled-Reasoning-math
GPT-oss-120B-Distilled-Reasoning-math Dataset
Data Source Model: gpt-oss-120bTask Type: Mathematical Problem SolvingData Format: JSON Lines
Fields: Generator, Category, Input, CoT_Native_Reasoning, Reasoning, Answer
Core Statistics
Generated complete reasoning processes and answers using gpt-oss-120b (MXFP4).The text length of the dataset reflects the depth and complexity of its content. I have statistically analyzed the lengths of the input (question), Reasoning, and… See the full description on the dataset page: https://huggingface.co/datasets/Jackrong/GPT-OSS-120B-Distilled-Reasoning-math.gpt-oss-120B-distilled-reasoning
GPT-oss-120B-Distilled-Reasoning-math Dataset
Data Source Model: gpt-oss-120bTask Type: Mathematical Problem SolvingData Format: JSON Lines
Fields: Generator, Category, Input, Output
Core Statistics
Generated complete reasoning processes and answers using gpt-oss-120b (MXFP4).The text length of the dataset reflects the depth and complexity of its content. I have statistically analyzed the lengths of the input (question), Reasoning, and Answer.To understand the data… See the full description on the dataset page: https://huggingface.co/datasets/Jackrong/gpt-oss-120B-distilled-reasoning.cemig-normas-v2-judged-50-gpt-oss-120b
CEMIG Distribution Standards Grounded QA Benchmark
Dataset summary
This dataset contains 50 synthetic, multi-context question-answer pairs grounded
in publicly classified CEMIG technical distribution standards. It was created to
evaluate retrieval-augmented generation (RAG) and grounded question answering in
the electrical-distribution domain. Each question and reference answer is in
English and is associated with two Portuguese source passages, retrieval… See the full description on the dataset page: https://huggingface.co/datasets/huglabs/cemig-normas-v2-judged-50-gpt-oss-120b.MuSeR_GPT_OSS_120B_DistillationThis dataset contains ~100k synthetic medical queries and corresponding responses distilled from GPT-OSS-120B.
The generation of synthetic medical queries follows an attribute-conditioned generation method proposed in paper Enhancing the Medical Context-Awareness Ability of LLMs via Multifaceted Self-Refinement Learning.
We found that supervised fine-tuning on this dataset can substantially improve LLMs' medical conversational capabilities. See our paper and project page for more details.
If… See the full description on the dataset page: https://huggingface.co/datasets/zyx1234/MuSeR_GPT_OSS_120B_Distillation.GPT-OSS-20B-Distilled-Reasoning-Mini
Dataset Card for Dataset Name
GPT-OSS-20B Distilled Reasoning Dataset Mini
(Multi-stage Evaluative Refinement Method for Reasoning Generation)
Dataset Details and Description
This is a high-quality instruction fine-tuning dataset constructed through knowledge distillation, featuring detailed Chain-of-Thought (CoT) reasoning processes. The dataset is designed to enhance the capabilities of smaller language models in complex reasoning, logical analysis, and instruction… See the full description on the dataset page: https://huggingface.co/datasets/Jackrong/GPT-OSS-20B-Distilled-Reasoning-Mini.gpt-oss-120B-distilled-math-OpenAI-Harmony
📚 Dataset Overview
Data Source Model: gpt-oss-120bTask Type: Mathematical Problem SolvingData Format: JSON Lines (.jsonl)Fields: Generator, Category, Input, Output
Note: If you are using this template for training, please make sure the format is correct before starting.Since this template is still under continuous improvement and learning, it may not be fully complete yet. I appreciate your understanding.
📈 Core Statistics
Generated complete reasoning processes… See the full description on the dataset page: https://huggingface.co/datasets/Jackrong/gpt-oss-120B-distilled-math-OpenAI-Harmony.eurorad-gpt-oss-training-data
Benchmarking and Adapting On-Device Large Language Models for Clinical Decision Support
Authors
Alif Munim* 1,
Jun Ma* 1,2,
Omar Ibrahim* 1,
Alhusain Abdalla* 1,
Shuolin Yin3,
Leo Chen4,
Bo Wang† 1,5,6,7,8
* Equal contribution † Corresponding author
1AI Collaborative Centre, University Health Network, Toronto, Canada
2Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
3Department of… See the full description on the dataset page: https://huggingface.co/datasets/wanglab/eurorad-gpt-oss-training-data.s1K-1.1-gpt-oss-20b
s1K-1.1-gpt-oss-20b
Dataset Summary
The s1K-1.1-gpt-oss-20b dataset extends the simplescaling/s1K-1.1 dataset by incorporating reasoning trajectories generated by the openai/gpt-oss-20b model. This dataset contains questions primarily from mathematical problem-solving domains, along with responses and reasoning trajectories generated by the gpt-oss-20b model. The dataset is designed to facilitate research into model reasoning capabilities, test-time scaling, and… See the full description on the dataset page: https://huggingface.co/datasets/IIGroup/s1K-1.1-gpt-oss-20b.gpt-oss-distilled-redteam2k
GPT-OSS Distilled RedTeam-2K Dataset
This is a preliminary experimental subset of a larger dataset. For the full dataset and additional information, see: Nemotron Nano 2 Safety Distill — GPT-OSS
.
⚠️ Content Warning: This dataset contains potentially harmful or policy-violating prompts (e.g., animal abuse, violence, privacy violations). The content includes sensitive safety-related queries and should be used responsibly for research purposes only.
Overview
This… See the full description on the dataset page: https://huggingface.co/datasets/Ericwang/gpt-oss-distilled-redteam2k.gpt-oss-benchmark-responses
gpt-oss-20b Benchmark Responses Dataset
Overview
This dataset contains responses generated by the gpt-oss-20b model on multiple benchmark tests, showcasing its performance in mathematical reasoning, language understanding, and cross-domain knowledge tasks. All responses are generated with a maximum length of 16K tokens.
The included benchmarks are:
(TODO) HLE (Humanity's Last Exam): A multimodal benchmark with 2,500 multiple-choice and short-answer questions spanning… See the full description on the dataset page: https://huggingface.co/datasets/IIGroup/gpt-oss-benchmark-responses.eurorad-gpt-oss-training-data
Eurorad Medical Radiology Training Dataset with GPT-OSS 120B Reasoning
Training dataset used for fine-tuning GPT-OSS 20B for medical radiology diagnosis tasks.
Dataset Description
This dataset contains 1,894 medical radiology cases from Eurorad, each enhanced with detailed diagnostic reasoning generated by GPT-OSS 120B. The dataset was used to train the model available at omareng/on-device-LLM-gpt-oss-20b.
Dataset Structure
Each row contains:
case_id: Unique… See the full description on the dataset page: https://huggingface.co/datasets/omareng/eurorad-gpt-oss-training-data.Synthetic-Quantum-Reasoning-GPTOSS120b
Synthetic Quantum Reasoning Dataset (GPT-OSS 120B)
A synthetic dataset of 4,881 quantum physics reasoning chains generated using GPT-OSS 120B.
Dataset Description
Each sample contains:
instruction: A quantum physics problem/question
output: A detailed reasoning chain with <think> and <answer> tags
Format
{
"instruction": "Consider a two-qubit system...",
"output": "<think>\nStep 1: ...\n</think>\n\n<answer>\n...\n</answer>"
}
Statistics… See the full description on the dataset page: https://huggingface.co/datasets/Kylan12/Synthetic-Quantum-Reasoning-GPTOSS120b.reasoning-sft-Superior-Reasoning-SFT-gpt-oss-120b-434K
Superior-Reasoning-SFT-gpt-oss-120b (converted)
Converted version of Alibaba-Apsara/Superior-Reasoning-SFT-gpt-oss-120b, combining both Stage 1 (~105k) and Stage 2 (~330k) into a single parquet file.
Format
Each row has three columns:
input — list of dicts [{"role": "user", "content": "..."}]
response — teacher-generated response string (includes <think> reasoning block)
domain — task domain (math, code, science, etc.)
License
CC BY 4.0
Credits… See the full description on the dataset page: https://huggingface.co/datasets/AmanPriyanshu/reasoning-sft-Superior-Reasoning-SFT-gpt-oss-120b-434K.gpt-oss-reasoning-ru-mediumНовая версия датасета на 25к строк
GPT-OSS-120B-Reasoning
OctoMed/GPT-OSS-120B-Reasoning
Single-turn instruction-following examples with explicit chain-of-thought reasoning,
converted to OctoMed format for SFT training.
Source
Derived from Jackrong/gpt-oss-120b-Reasoning-Instruction
by Jackrong. All credit for the original data collection and
model distillation goes to the original authors.
Format
Each example contains:
question: the instruction / question text
answer: the final answer extracted after reasoning… See the full description on the dataset page: https://huggingface.co/datasets/OctoMed/GPT-OSS-120B-Reasoning.Medical-Reasoning-SFT-GPT-OSS-120B-V2
Medical-Reasoning-SFT-GPT-OSS-120B-V2
A large-scale medical reasoning dataset generated using openai/gpt-oss-120b, containing over 506,000 samples with detailed chain-of-thought reasoning for medical and healthcare questions.
GPT-OSS-120B is OpenAI's state-of-the-art open-weight model, achieving near-parity with closed models on reasoning benchmarks while being Apache 2.0 licensed.
Dataset Overview
Metric
Value
Model
openai/gpt-oss-120b
Total Samples
506… See the full description on the dataset page: https://huggingface.co/datasets/introvoyz041/Medical-Reasoning-SFT-GPT-OSS-120B-V2.gpt-oss-reasoning-ru-nanoВторая версия датасета на 1000 примеров.